spaCy/website/usage/_processing-pipelines/_extensions.jade

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//- 💫 DOCS > USAGE > PROCESSING PIPELINES > DEVELOPING EXTENSIONS
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| We're very excited about all the new possibilities for community
| extensions and plugins in spaCy v2.0, and we can't wait to see what
| you build with it! To get you started, here are a few tips, tricks and
| best practices. For examples of other spaCy extensions, see the
| #[+a("/usage/resources#extensions") resources].
+list
+item
| Make sure to choose a #[strong descriptive and specific name] for
| your pipeline component class, and set it as its #[code name]
| attribute. Avoid names that are too common or likely to clash with
| built-in or a user's other custom components. While it's fine to call
| your package "spacy_my_extension", avoid component names including
| "spacy", since this can easily lead to confusion.
+code-wrapper
+code-new name = 'myapp_lemmatizer'
+code-old name = 'lemmatizer'
+item
| When writing to #[code Doc], #[code Token] or #[code Span] objects,
| #[strong use getter functions] wherever possible, and avoid setting
| values explicitly. Tokens and spans don't own any data themselves,
| so you should provide a function that allows them to compute the
| values instead of writing static properties to individual objects.
+code-wrapper
+code-new.
is_fruit = lambda token: token.text in ('apple', 'orange')
Token.set_extension('is_fruit', getter=is_fruit)
+code-old.
token._.set_extension('is_fruit', default=False)
if token.text in ('apple', 'orange'):
token._.set('is_fruit', True)
+item
| Always add your custom attributes to the #[strong global] #[code Doc]
| #[code Token] or #[code Span] objects, not a particular instance of
| them. Add the attributes #[strong as early as possible], e.g. in
| your extension's #[code __init__] method or in the global scope of
| your module. This means that in the case of namespace collisions,
| the user will see an error immediately, not just when they run their
| pipeline.
+code-wrapper
+code-new.
from spacy.tokens import Doc
def __init__(attr='my_attr'):
Doc.set_extension(attr, getter=self.get_doc_attr)
+code-old.
def __call__(doc):
doc.set_extension('my_attr', getter=self.get_doc_attr)
+item
| If your extension is setting properties on the #[code Doc],
| #[code Token] or #[code Span], include an option to
| #[strong let the user to change those attribute names]. This makes
| it easier to avoid namespace collisions and accommodate users with
| different naming preferences. We recommend adding an #[code attrs]
| argument to the #[code __init__] method of your class so you can
| write the names to class attributes and reuse them across your
| component.
+code-wrapper
+code-new Doc.set_extension(self.doc_attr, default='some value')
+code-old Doc.set_extension('my_doc_attr', default='some value')
+item
| Ideally, extensions should be #[strong standalone packages] with
| spaCy and optionally, other packages specified as a dependency. They
| can freely assign to their own #[code ._] namespace, but should stick
| to that. If your extension's only job is to provide a better
| #[code .similarity] implementation, and your docs state this
| explicitly, there's no problem with writing to the
| #[+a("#custom-components-user-hooks") #[code user_hooks]], and
| overwriting spaCy's built-in method. However, a third-party
| extension should #[strong never silently overwrite built-ins], or
| attributes set by other extensions.
+item
| If you're looking to publish a model that depends on a custom
| pipeline component, you can either #[strong require it] in the model
| package's dependencies, or if the component is specific and
| lightweight choose to #[strong ship it with your model package]
| and add it to the #[code Language] instance returned by the
| model's #[code load()] method. For examples of this, check out the
| implementations of spaCy's
| #[+api("util#load_model_from_init_py") #[code load_model_from_init_py()]]
| and #[+api("util#load_model_from_path") #[code load_model_from_path()]]
| utility functions.
+code-wrapper
+code-new.
nlp.add_pipe(my_custom_component)
return nlp.from_disk(model_path)
+item
| Once you're ready to share your extension with others, make sure to
| #[strong add docs and installation instructions] (you can
| always link to this page for more info). Make it easy for others to
| install and use your extension, for example by uploading it to
| #[+a("https://pypi.python.org") PyPi]. If you're sharing your code on
| GitHub, don't forget to tag it
| with #[+a("https://github.com/topics/spacy?o=desc&s=stars") #[code spacy]]
| and #[+a("https://github.com/topics/spacy-extension?o=desc&s=stars") #[code spacy-extension]]
| to help people find it. If you post it on Twitter, feel free to tag
| #[+a("https://twitter.com/" + SOCIAL.twitter) @#{SOCIAL.twitter}]
| so we can check it out.